metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
base_model: roberta-base
model-index:
  - name: run-5
    results: []

run-5

This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.2694
Accuracy: 0.745
Precision: 0.7091
Recall: 0.7017
F1: 0.7043

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.9558	1.0	50	0.8587	0.665	0.6541	0.6084	0.5787
0.7752	2.0	100	0.8892	0.655	0.6416	0.5835	0.5790
0.5771	3.0	150	0.7066	0.715	0.6884	0.7026	0.6915
0.3738	4.0	200	1.0130	0.705	0.6578	0.6409	0.6455
0.253	5.0	250	1.1405	0.74	0.7132	0.7018	0.7059
0.1604	6.0	300	1.1993	0.69	0.6334	0.6244	0.6261
0.1265	7.0	350	1.5984	0.705	0.6875	0.6775	0.6764
0.0741	8.0	400	1.4755	0.745	0.7116	0.7132	0.7114
0.0505	9.0	450	2.2514	0.71	0.6791	0.6427	0.6524
0.0372	10.0	500	2.2234	0.71	0.6675	0.6503	0.6488
0.0161	11.0	550	2.1070	0.72	0.6783	0.6712	0.6718
0.016	12.0	600	2.0232	0.72	0.6737	0.6659	0.6688
0.0197	13.0	650	2.0224	0.74	0.7065	0.6954	0.6895
0.01	14.0	700	2.1777	0.74	0.7023	0.6904	0.6936
0.0173	15.0	750	2.3227	0.72	0.6761	0.6590	0.6638
0.0066	16.0	800	2.2131	0.735	0.6983	0.6912	0.6923
0.0043	17.0	850	2.1196	0.76	0.7278	0.7207	0.7191
0.0039	18.0	900	2.4087	0.72	0.6791	0.6590	0.6650
0.0041	19.0	950	2.1487	0.73	0.6889	0.6860	0.6873
0.0024	20.0	1000	2.2694	0.745	0.7091	0.7017	0.7043

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu116
Tokenizers 0.13.2